Instructions to use oyemade/whisper-small-yo-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oyemade/whisper-small-yo-onnx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="oyemade/whisper-small-yo-onnx")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("oyemade/whisper-small-yo-onnx") model = AutoModelForSpeechSeq2Seq.from_pretrained("oyemade/whisper-small-yo-onnx", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download onnx/decoder_with_past_model_quantized.onnx from oyemade/whisper-small-yo-onnx: direct link, hf CLI and curl.
- Browser
- Download file 142 MB
-
https://huggingface.co/oyemade/whisper-small-yo-onnx/resolve/main/onnx/decoder_with_past_model_quantized.onnx
- Command line
-
hf download hf://oyemade/whisper-small-yo-onnx/onnx/decoder_with_past_model_quantized.onnx
-
curl -L -o decoder_with_past_model_quantized.onnx https://huggingface.co/oyemade/whisper-small-yo-onnx/resolve/main/onnx/decoder_with_past_model_quantized.onnx
142 MB
- Xet hash:
- 853ce8df7245d82f00caeec4024f2cf7fbb0183abe6eeedac488237aa24baab2
- Size of remote file:
- 142 MB
- SHA256:
- 2d0c755add87a4e074b872ebc566c45208eff67a7c6247c813d1e52a6d995294
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